Developing Trustworthy Artificial Intelligence (AI)-Driven Tools to Predict Vascular Disease Risk and Progression

Peripheral Arterial Disease Clinical Trial

— VASCULAIDRETRO  

Official title:

Developing Trustworthy Artificial Intelligence (AI)-Driven Tools to Predict Vascular Disease Risk and Progression

Clinical Trial Details — Status: Recruiting

Administrative data

• NCT number: NCT06206369
• Other study ID #: 2011279
• Status: Recruiting
• Start date: October 31, 2023
• Est. completion date: May 1, 2029

Study information

• Verified date: January 2024
• Source: Amsterdam UMC, location VUmc
• Contact: Kak Khee Yeung, MD, PhD
• Phone: +31 6 14278725
• Email: k.yeung[@]amsterdamumc.nl
• Is FDA regulated: No
• Study type: Observational

Clinical Trial Summary

The VASCULAID-RETRO study, within the broader VASCULAID project, aims to create artificial intelligence (AI) algorithms that can predict cardiovascular events and the progression of abdominal aortic aneurysm (AAA) and peripheral arterial disease (PAD). The study plans to gather and analyze data from at least 5000 AAA and 6000 PAD patients, combining existing cohorts and retrospectively collected data. During this project, AI tools will be developed to perform automatic anatomical segmentation and analyses on multimodal imaging. AI prediction algorithms will be developed based on multisource data (imaging, medical history, -omics).

Description:

To date, it is unknown which abdominal aortic aneurysm (AAA) and peripheral arterial disease (PAD) patients will suffer cardiovascular events or in which patients the AAA or PAD will progress. In the VASCULAID project, the VASCULAID-RETRO study aims to leverage data from existing cohorts and retrospectively collected data to develop artificial intelligence (AI) algorithms able to evaluate the risk of cardiovascular events and extent of disease progression.

In order to build and train the algorithms for the predictions, we plan to retrospectively enroll at least 5000 AAA and 6000 PAD patients AI-tools will be applied to the patient data. Automatic anatomical segmentation on images and image analysis on US, CTA and MRI will be performed. Also, algorithms to predict cardiovascular events and AAA or PAD progression based on multi-source data analysis will be developed.

Patient data from European clinical consortium partners is available. This consortium has access to big cohorts with relevant data for the envisioned study that will be used to enrich the existing registries. These data will be used to refine the algorithms developed for the prediction of cardiovascular events and AAA/PAD progression.

Recruitment information / eligibility

• Status: Recruiting
• Enrollment: 11000
• Est. completion date: May 1, 2029
• Est. primary completion date: May 1, 2029
• Accepts healthy volunteers: No
• Gender: All
• Age group: 40 Years to 90 Years

Eligibility

Inclusion Criteria:

• Males and females, 40-90 years old, with an AAA >3cm. This includes patients with infrarenal, juxtarenal, suprarenal, iliac (defined as 1.5x its normal diameter) aneurysms, as well as mycotic aneurysms. Patients that have had interventions or ruptures will also be included

• Males and females, 40-90 years old, all PAD patients (Fontaine stages 1,2,3, and 4).

Exclusion Criteria:

• Patients with an ascending, thoracic, thoracoabdominal (type 1-3) aneurysm.

Related Conditions & MeSH terms

• Aneurysm
• Aneurysm Abdominal
• Aortic Aneurysm, Abdominal
• Peripheral Arterial Disease
• Peripheral Vascular Diseases
• Vascular Diseases

Intervention

Other:
• No intervention, retrospective study
No intervention, retrospective study

Locations

Country	Name	City	State
Finland	Hospital District of Helsinki and Uusimaa (HUS)	Helsinki
Germany	Asklepios kliniken hamburg	Hamburg
Netherlands	Amsterdam UMC	Amsterdam
Portugal	University Hospital Center of São João	Porto
Serbia	University Clinical Centre of Serbia	Belgrade
United Kingdom	Oxford University Hospitals	Oxford

Sponsors (13)

Lead Sponsor

Collaborator

Amsterdam UMC, location VUmc

Academisch Medisch Centrum - Universiteit van Amsterdam (AMC-UvA), Asklepios Kliniken Hamburg GmbH, Brightfish Be, Centre Hospitalier Universitaire de Nice, Faculty of Medicine, University of Belgrade, Hospital District of Helsinki and Uusimaa, Stichting Allai, Technical University of Twente, Universidade do Porto, University of Bergen, University of Oxford, VINCA INSTITUTE OF NUCLEAR SCIENCES Belgrado

Countries where clinical trial is conducted

Finland,  Germany,  Netherlands,  Portugal,  Serbia,  United Kingdom, 

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Development of disease progression prediction algorithms	The primary goal of this retrospective study is to develop and train algorithms to predict disease progression and risk of cardiovascular events in AAA and PAD patients by leveraging multi-parametric data from 5000 AAA (>1000 in AUMC) and 6000 PAD (>1000 in AUMC) patients from existing cohorts and biobanks.	3 years
Secondary	Internal validation of disease progression prediction algorithms	The secondary objective will be the internal validation of the developed algorithms using data from retrospective cohorts.	3 years